Systems and methods for visualizing and analyzing a rail surface

ABSTRACT

A system for analyzing a railroad track comprises a transport device, a camera coupled to the transport device, an electronic display device, a memory device, and one or more processors. The camera is disposed adjacent to a rail of the railroad track and generates image data reproducible as one or more images of at least a portion of a surface of the rail. The processors can produce an image of the rail surface, which includes a plurality of elongated portions. The image is analyzed to identify any defects that exist within each elongated portion of the rail surface. The processors determine a value of a metric for each elongated portion of the rail surface. The metric is associated with the identified defects. The electronic display device displays a graph indicative of the metric for each elongated portion, the image of the rail surface, or both.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/632,656, filed Jan. 21, 2020, now allowed, which is a U.S. NationalStage Entry of International Application No. PCT/US2018/044212, filedJul. 27, 2018, which claims priority to and the benefit of U.S.Provisional Patent Application No. 62/538,894, filed Jul. 31, 2017, andU.S. Provisional Patent Application No. 62/538,531, filed Jul. 28, 2017,each of which is hereby incorporated by reference herein in itsentirety.

TECHNICAL FIELD

The present disclosure relates to rail inspection systems, and moreparticularly, to systems and methods for visualizing and analyzing arail surface.

BACKGROUND

Some prior practices categorize rail surface damage using pre-definedgrades, which can be subjective and can fail to represent the detailedmeasurement accurately. Other prior practices report overall summarystatistics over particular sections of the track, which fails toillustrate the detailed distribution of rail surface damage along thetrack on a foot-by-foot basis. The present disclosure is directed tosolving these problems and addressing other needs.

SUMMARY

A system for visualizing and quantifying surface damage of a railroadtrack comprises a transport device configured to travel along therailroad track; a camera coupled to the transport device such that thecamera is (i) disposed adjacent to a rail of the railroad track and (ii)configured to generate image data reproducible as an image of at least aportion of a surface of the rail; an electronic display device; a memorydevice configured to receive and store therein the generated image data;and one or more processors configured to: produce, based on the imagedata, an image of the surface of the rail, the surface of the rail inthe image including a plurality of elongated portions; analyze the imageto identify one or more defects within each of the plurality ofelongated portions of the surface of the rail; determine a value of atleast one metric for each of the plurality of elongated portions of thesurface of the rail, the at least one metric being associated with theidentified one or more defects within each of the plurality of elongatedportions of the surface of the rail; and cause the electronic displaydevice to display (i) the image of the surface of the rail, (ii) a graphindicative of the at least one metric for each of the plurality ofelongated portions of the surface of the rail, or both (i) and (ii).

A method for visualizing and quantifying surface damage of a railroadtrack comprises generating, via a camera disposed adjacent to a rail ofthe railroad track, image data; producing, based on the generated imagedata, an image of a surface of the rail, the surface of the rail in theimage including a plurality of elongated portions; analyzing the imageto identify one or more defects within each of the plurality ofelongated portions of the surface of the rail; determining a value of atleast one metric for each of the plurality of elongated portions of thesurface of the rail, the at least one metric being associated with theidentified one or more defects within each of the plurality of elongatedportions of the surface of the rail; and causing an electronic displaydevice to display (i) the image of the surface of the first rail, (ii) agraph indicative of the at least one metric for each of the plurality ofelongated portions of the surface of the rail, or both (i) and (ii).

A system for visualizing and quantifying surface damage of a railroadtrack comprises a transport device configured to travel along therailroad track; a first camera coupled to the transport device such thatthe first camera is (i) disposed adjacent to a first rail of therailroad track and (ii) configured to generate first image datareproducible as a first image of a portion of a surface of the firstrail; a second camera coupled to the transport device such that thesecond camera is (i) disposed adjacent to a second rail of the railroadtrack and (ii) configured to generate second image data reproducible asa second image of a portion of a surface of the second rail; anelectronic display device; a memory device configured to receive andstore therein the generated first image data and the generated secondimage data; and one or more processors configured to: divide the firstimage of the portion of the surface of the first rail into a firstplurality of regions; divide the second image of the portion of thesurface of the second rail into a second plurality of regions; analyzethe divided first image to identify, within each of the first pluralityof regions, one or more defects in the portion of the surface of thefirst rail; analyze the divided second image to identify, within each ofthe second plurality of regions, one or more defects in the portion ofthe surface of the second rail; determine information associated withthe identified one or more defects in the portion of the surface of thefirst rail and the identified one or more defects in the portion of thesurface of the second rail; and cause the electronic display device todisplay (i) at least a portion of the first image, (ii) at least aportion of the second image, (iii) the determined information associatedwith the identified one or more defects in the portion of the surface ofthe first rail, (iv) the determined information associated with theidentified one or more defects in the portion of the surface of thesecond rail, or (v) any combination of (i), (ii), (iii), or (iv).

A system for visualizing and quantifying surface damage of a railroadtrack comprises a transport device configured to travel along therailroad track; a camera coupled to the transport device such that thecamera is (i) disposed adjacent to a rail of the railroad track and (ii)configured to generate image data reproducible as an image of a surfaceof the rail; an electronic display device; a memory device configured toreceive and store therein the generated image data; and one or moreprocessors configured to: produce, based on the image data, a pluralityof first images, each of the plurality of first images being of arespective elongated portion of the surface of the rail; analyze theplurality of first images to identify one or more defects in the surfaceof the rail within each of the elongated portions of the surface of therail; determine a value of at least one metric for each of the elongatedportions of the surface of the rail, the at least one metric beingassociated with the identified one or more defects in the surface of therail within each respective one of the elongated portions of the surfaceof the rail; and cause the electronic display device to display (i) asecond image including each of the elongated portions of the surface ofthe rail and (ii) a graph indicative of the at least one metric for eachof the elongated portions of the surface of the rail.

The foregoing and additional aspects and implementations of the presentdisclosure will be apparent to those of ordinary skill in the art inview of the detailed description of various embodiments and/orimplementations, which is made with reference to the drawings, a briefdescription of which is provided next.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other advantages of the present disclosure will becomeapparent upon reading the following detailed description and uponreference to the drawings.

FIG. 1 is a block diagram of the components of a system for visualizingand analyzing a rail surface;

FIG. 2A is a perspective view of a first implementation of the system ofFIG. 1;

FIG. 2B is an end view of a second implementation of the system of FIG.1;

FIG. 3A is a partial perspective view of cameras and light sources ofthe system of FIG. 1 aimed at two rails;

FIG. 3B is a partial end view of the cameras and light sources of FIG.3A;

FIG. 3C is a partial side view of the cameras and light sources of FIG.3A;

FIG. 4A is an image of a portion of a rail surface generated by thesystem of FIG. 1;

FIG. 4B is an image of the portion of the rail surface of FIG. 4Adivided into a plurality of regions;

FIG. 5 is an image of an electronic display device displaying an imageof the surfaces of two rails, cross-sectional images of the two rails,and graphs of information related to the two rails; and

FIG. 6 is a flow diagram of a method for visualizing and analyzing arail surface.

While the present disclosure is susceptible to various modifications andalternative forms, specific implementations and embodiments have beenshown by way of example in the drawings and will be described in detailherein. It should be understood, however, that the present disclosure isnot intended to be limited to the particular forms disclosed. Rather,the present disclosure is to cover all modifications, equivalents, andalternatives falling within the spirit and scope of the presentdisclosure as defined by the appended claims.

DETAILED DESCRIPTION

Referring now to FIG. 1, a system 10 for visualizing and quantifyingsurface damage on a railroad track includes a transport device 12, oneor more cameras 14, one or more light sources 16, one or more processors18, one or more memory devices 20, and an electronic display device 22.The transport device 12 is configured to travel along the track. Thecameras 14 and the light sources 16 are coupled to the transport device12 and are aimed at the surface of the rails of the railroad track. Thelight sources 16 illuminate the surface of the rails while the cameras14 generate image data that is reproducible as images of the surface ofthe rails.

The one or more memory devices 20 are coupled to the one or more cameras14, and can receive and store the image data that is generated by thecameras 14. The one or more processors 18 are coupled to the memorydevices 20 and are used to analyze the image data generated by thecameras 14. In some implementations, the processors 18, the memorydevices 20, or both are located in the transport device 12. In otherimplementations, one or both of the processor 18 and the memory devices20 are located external to the transport device 12. In still otherimplementations, the processors 18 and the memory devices 20 can belocated in the transport device 12, and any of the images or datacaptured or produced by the system 10 can be transmitted to otherprocessors and/or memory devices located external to the transportdevice 12.

The analysis of the surfaces of the rails as discussed herein can takeplace in the transport device 12, external to the transport device 12,or both. For example, the processors 18 and memory devices 20 in thetransport device 12 can perform the analysis, and communicate theanalysis to an external device or location, such as a hard drive, amobile device, a tablet computer, a laptop computer, a desktop computer,an Internet-connected storage device, etc. In some implementations, theanalysis is communicated to an external source that is located within avehicle traveling alongside the transport device 12 as the transportdevice 12 travels along the railroad track. In other implementations,the processors 18 and memory device on the transport device 12immediately communicate the data to the external device or locationwithout performing the analysis, which can then be performed by theexternal device or at the external location.

As is discussed in more detail herein, the processors 18 are configuredto produce images of the surface of the rail and analyze the images toidentify defects in the surface of the rail. The processors 18 can thendetermine a variety of information associated with the defects. Thisinformation can be damage metrics that are used to quantify thecondition of the surface of the rails. In some implementations, theimages are produced and analyzed in real-time as the transport device 12travels along the tracks. In other implementations, the images areproduced and analyzed after the transport device 12 has traveled alongthe length of the track.

It should be understood that defect generally refers to any type ofdamage, mark, or other feature that may occur to or be located on thesurface of the rail, such as cracks, pitting, etc., whether or not thedefects require the rails to be repaired or replaced. Rather, thedefects are used to calculate various metrics that indicate thecondition of the rail, which can be used to determine whether the railsneed to be repaired or replaced. Other types of metrics can also becalculated and used. The processors 18 can also determine a variety ofinformation about properties of the rails themselves, includingstructural properties or the identification of grinding marks.

In some implementations, the cameras 14 are triggered to generate imagedata by rotation of the wheels of the transport device 12. As thetransport device 12 moves along the tracks and the wheels rotates, thecameras 14 can continuously generate image data of the surface of therails. In some implementations, if the transport 12 device stops for anyreasons, the cameras 14 pause so they do not generate image data whilethe transport device 12 is stopped. This prevents redundant image datafrom being generated. The cameras 14 can be line-scan cameras, framecameras, photodiodes, photomultiplier tube arrays, charge-coupleddevices (CCDs), etc. The light sources 16 can be any light source thatis able to illuminate the portion of the surface of the rail that thecameras 14 are currently aimed at. The light sources 16 can includefluorescent bulbs, incandescent bulbs, light emitting diodes (LEDs), arclamps, flashtubes, etc.

While the system 10 is generally used to analyze the surfaces ofrailroad tracks, the system 10 can be used to analyze any type of trackupon which a vehicle can travel. For example, the system 10 could beused with subway tracks, elevated train tracks, high speed rail tracks,monorail tracks, tram tracks, etc. The system 10 can also be adapted towork with tracks having any number of rails. While reference isgenerally made herein to a railroad track having left and right rails,the system 10 can be used to analyze single-rail tracks, or tracks withtwo or more rails.

As shown in FIG. 2A and FIG. 2B, the cameras and the light sources canbe mounted to the underside of the transport device 12 so that thecameras and light sources are disposed above the rails. The cameras andthe light sources can be positioned within a housing 24 (FIG. 2A) orhousing portions 25A and 25B (FIG. 2B) to protect them during use. Thecameras and the light sources point downward toward the left rail 26Aand the right rail 26B. The cameras and the light sources aimed at rail26A are all generally aimed at the same location along the surface ofrail 26A. Similarly, the cameras and the light sources aimed at rightrail 26B are all generally aimed at the same location along the surfaceof rail 26B. The light sources thus illuminate the surface of the rails26A, 26B as the cameras generate image data that can be reproduced asimages of the surfaces of the rails 26A, 26B.

Any number of different types of vehicles can be used as the transportdevice 12. For example, the transport 12 device may be a truck that isconfigured to move along the railroad track. The transport device 12could also be a train car. These vehicles could be standard trucks ortrain cars, or could be specially modified to travel along the track.Generally, any device that can be configured to move along the railroadtrack can be used as the transport device 12.

Referring now to FIGS. 3A-3C, the one or more cameras generally includesa first camera 14A and a second camera 14B coupled to the transportdevice. The first camera 14A is mounted above the left rail 26A of therail track. The second camera 14B is mounted above the right rail 26B ofthe rail track. Each rail 26A, 26B comprises a rail base 28A and 28B, arail web 30A and 30B, and a rail head 32A and 32B. The rail base 28A,28B of each rail 26A, 26B rests on one or more crossties 36, whichgenerally span at least the distance between the rails 26A, 26B. Whenthe transport device travels along the rails 26A, 26B, the wheels of thetransport device rest on surfaces 34A and 34B of the rail heads 32A,32B. The rail head surfaces 34A, 34B of each rail 26A, 26B are bothgenerally curved along the width of the rail head surfaces 34A, 34B toform a slight arch with respect to the ground. However, in someimplementations, the rail head surfaces 34A, 34B are flat.

Camera 14A is generally aimed only at rail 26A, while camera 14B isgenerally aimed only at rail 26B. However, some implementations one ormore of the cameras could be aimed at multiple rails. Each camera 14A,14B is spaced apart from its respective rail 26A, 26B along a respectivevertical axis A₁ and A₂. These axes extend upwards from the rail headsurfaces 34A, 34B of rails 26A, 26B respectively. Axes A₁ and A₂ arealso each generally perpendicular to the rail head surfaces 34A, 34B.However, because the rail head surfaces 34A, 34B can be curved, axes A₁and A₂ may not be perpendicular to the rail head surfaces 34A, 34B atevery point along the rail head surfaces 34A, 34B. However, axes A₁ andA₂ are generally perpendicular at least to the center of the rail headsurfaces 34A, 34B. Furthermore, while axes A₁ and A₂ are referred to asvertical axes for ease of understanding, depending on the layout of thetrack and its relation to the ground, axes A₁ and A₂ may not always becompletely vertical.

Axes A₁ and A₂ are also each generally perpendicular to both atransverse axis B (which extends between and connects the rails 26A,26B) and a longitudinal axis C (which extends along the length of therails 26A, 26B). As best shown in FIG. 3B, cameras 14A and 14B aregenerally mounted inwardly relative to rails 26A and 26B, respectively.In this manner, camera 14A is further spaced apart from rail 26A alongthe second axis B towards rail 26B. Similarly, camera 14B is furtherspaced apart from rail 26B along the second axis B towards rail 26A.Cameras 14A and 14B are thus positioned at angles θ₁ and θ₂ relative toaxes A₁ and A₂, respectively. In some implementations, angles θ₁ and θ₂can be between about 0.1° and about 20°, between about 5.0° and about12.0°, or about 5.0°. Both of the cameras 14A and 14B can be mounted atthe same angle relative to their respective vertical axes A₁ and A₂, orthey could each be mounted at different angles relative to axes A₁ andA₂. In some implementations, one or both of cameras 14A, 14B could bemounted at an angle of 0° relative to their respective vertical axes A₁and A₂, e.g., the cameras 14A, 14B could be mounted directly over therail head surfaces 34A, 34B.

Regardless of the angle θ₁, θ₂ at which cameras 14A, 14B are disposed atrelative to the vertical axis, cameras 14A, 14B are generally alwaysaimed at the rail head surfaces 34A and 34B. Thus, camera 14A and 14Bare not always aimed directly downward with respect to where they arecoupled to transport device at, e.g., parallel to axes A₁ and A₂respectively. Rather, cameras 14A and 14B are generally aimed outwardtowards rails 26A, 26B respectively. Camera 14A is thus aimed at anangle back towards rail head surface 34A, while camera 14B is aimed atangle back towards rail head surface 34B. These angles are generallyequal to angles θ₁ and θ₂, respectively. However, in someimplementations, these angles are different from angles θ₁ and θ₂,respectively.

The camera 14A, 14B are generally positioned inwardly and aimedoutwardly with respect to rails 26A and 26B to ensure that the imagesthat are produced from the generated image data clearly show the innerareas of the rail head surfaces 34A, 34B closer the inner edges of rails26A, 26B. Most vehicles that travel along tracks, such as a train cartraveling along a railroad track, have wheels with inner flanges thatextend downward along the inner side of the rails 26A, 26B. As a result,there is generally more contact between the wheels and the inner areasof the rail head surfaces 34A, 34B that are closer to the inner edges ofthe rails 26A, 26B. These inner areas of the rail head surfaces 34A, 34Bcan be damaged more easily, and thus it is important to produce imagesthat fully show these inner areas. Because the rail head surfaces 34A,34B can be slightly arched with respect to the ground, the areas of therail head surfaces 34A, 34B closest to the inner edges of the rails 26A,26B curve away from cameras mounted directly overhead. By angling thecamera 14A, 14B inwardly and aiming them outwardly, the images that areproduced fully capture the areas of the rail head surfaces 34A, 34Bnearest the inner edges of the rails 26A, 26B.

FIGS. 3A-3C also illustrate the arrangement of the one or more lightsources relative to the rail head surfaces 34A, 34B. Each light sourceis configured to aid in illuminating the portion of the rail headsurface 34A, 34B that one of the cameras is aimed at. As shown, the oneor more light sources can include first and second light sources 16A and16B that illuminate the rail head surface 34A of rail 26A. The one ormore light sources further include third and fourth light sources 16Cand 16D that illuminate the rail head surface 34B of rail 26B. The firstand second lights sources 16A and 16B are spaced apart from rail 26Aalong axis A₁, while third and fourth light sources 16C and 16D arespaced apart from rail 26B along axis A₂. In some implementations, thelight sources 16A-16D are disposed at about the same vertical positionas their respective cameras 14A, 14B. In other implementations however,the light sources 16A-16D are disposed nearer to or further away fromthe rail head surfaces 34A, 34B as compared to cameras 14A, 14B.

Unlike cameras 14A and 14B however, light sources 16A-16D are generallynot spaced apart from the rail along axis B. As such, the light sources16A-16D are generally not angled inwardly or outwardly with respect torails 26A, 26B. However, light sources 16A-16D are spaced apart alongaxis C from the portion of the rail head surfaces 34A, 34B that lightsources 16A-16D are illuminating. Light sources 16A-16D are thus aimedat an angle toward rail head surfaces 34A, 34B. As best shown in FIG.3C, light sources 16A and 16B are spaced apart along the length of rail26A from the portion of the rail head surface 34A that they areilluminating. In this manner, light source 16A is spaced apart in afirst direction along axis C, while light source 16B is spaced apart ina second direction along axis C opposite the first direction. The lightsources 16A and 16B are thus disposed at angles relative to axis A₁.Light sources 16A, 16B are also aimed back towards rail head surface 34Aat corresponding angles.

While not shown in FIG. 3C, light sources 16C and 16D are arrangedsimilarly. The light sources 16C and 16D are spaced apart in oppositedirections along axis C from the portion of rail head surface 34B thatthey are illuminating. As such, light sources 16C and 16D are alsodisposed at angles relative to axis A₂, and aimed back towards rail headsurface 34B at corresponding angles. In some implementations, one ormore of the light sources 16A-16D are disposed at an angle of about 13°.In other implementations, these angles are between about 10° and about15°, between about 5° and about 20°, or between about 0° and about 30°.

In some implementations, light sources 16A and 16B are disposed atdifferent angles relative to axis A₁, and light sources 16C and 16D aredisposed at different angles relative to axis A₂. The sum of the anglesat which light sources 16A and 16B are disposed can be less than about60.0°, between about 20° and about 30°, between about 10° and about 40°,or about 26.0°. In some implementations, light sources 16C and 16D aredisposed in a similar arrangement as light sources 16A and 16B. In otherimplementations, light sources 16C and 16D can be disposed in adifferent arrangement than light sources 16A and 16B.

Other implementations can have any number or arrangement of lights andcameras. For example, some implementations include a single camera witha field of view wide enough to image all the rails of the track. Otherimplementations could include multiple cameras per rail. Still otherimplementations could modify the angle at which the cameras arepositioned relative to the rail. For example, some implementations couldhave the cameras mounted directly above the rails and aimed straightdown, or mounted outwardly from the rails and aimed inwardly.Implementations including multiple cameras per rail could have eachcamera for a rail disposed between the rails, or could have one cameradisposed at an inward angle, one camera disposed directly above therails, one camera disposed at an outward angle, etc. In otherimplementations, all of the cameras can be mounted at aimed at its ownrespective angle, which may be the same or different as the angle in oneor more of the other cameras.

Some implementations include only a single light source per rail. Otherimplementations could include a single light source that illuminatesboth rails. The light sources can have a focused beam of light that hasa width approximately equal to the width of the rail head surfaces. Inother implementations, the width of the beam of light produced by thelight sources is wider than the width of the rail head surfaces. Similarto the cameras, each light source can be mounted and aimed at an anglethat can be the same or different from the angle of each of the otherlight sources.

Referring now to FIG. 4A and FIG. 4B, as the transport device travelsalong the rail and generates image data, the processors of the systemcan generate one or more images of the rail head surfaces 34A, 34B. Insome implementations, a single image of both rail head surfaces 34A, 34Bis produced. In other implementations, a first image is produced thatshows rail head surface 34A, and a second image is produced that showsrail head surface 34B. In implementations analyzing tracks with morethan two rails, a single image can be produced that shows all of therails, or multiple images that show one or more rails can be produced.In other implementations, the image or images may be of discreteelongated portions of the rail head surfaces 34A, 34B along thelongitudinal direction (e.g., the length) of the rail. In theimplementation of FIG. 4A, the image 40 is of a single discreteelongated portion of rail head surface 34A. Generally, any number ofimages 40 can be produced showing some or all portions of one or more ofthe rails of the track.

Once the image or images of the rail head surfaces 34A, 34B areproduced, each discrete elongated portion along the length of the railhead surfaces 34A, 34B can be analyzed individually. Each discreteelongated portion of the rail head surfaces 34A, 34B that is analyzedhas a length equal to a unit length l. Each rail 26A, 26B of a trackbeing analyzed that has a total length L will thus have a number ofdiscrete elongated portions equal to L/l. In some implementations, theunit length l is about one foot. In other implementations, the unitlength l is between about one half foot and about two feet. Generally,the unit length l can be modified as needed for the current applicationof the system.

Image 40 of the rail head surface 34A can show a variety of differentdefects that are present in the single discrete elongated portion of therail head surface 34A. These defects can include cracks, pittingdefects, grinding marks, etc. The processors of the system areconfigured to analyze the image 40 and detect the edges of the rail headsurface 34A using computer vision techniques. In some implementationsthe processors also determine which edge is the inner edge and whichedge is the outer edge. In other implementations, it is known prior tothe analysis which edge is the inner edge and which edge is the outeredge. After the edges of the rail head surface 34A are identified, thewidth of the portion of the rail head surface 34A can be measured. Thewidth of the rail head surface 34A is generally equal to the distancebetween the inner edge and the outer edge of rail head surface 34A.

After the width of the rail head surface 34A has been determined, theprocessors of the system are configured to divide the discrete elongatedportion of the rail head surface 34A in the image 40 that is beinganalyzed to create a divided image 50, as shown in FIG. 4B. In thedivided image 50, the discrete elongated portion of rail head surface34A has been divided into one or more regions 52A-52D for analysispurposes. As shown, the portion of the rail head surface 34A is dividedinto regions 52A-52D along the width of the rail head surface 34A. Eachregion 52A-52D has a width that is generally less than the total widthof the rail head surface 34A in the image 40. Each region 52A-52D alsohas a length that is generally equal to the unit length l of thediscrete elongated portion of the rail head surface 34A. By dividing theimage of the rail head surface 34A into the plurality of regions52A-52D, the system can determine information about each region 52A-52Dof the rail head surface 34A. As is discussed herein, this informationcan include a number of metrics, including damage metrics related todefects in the rail head surface 34A.

Divided image 50 shows the rail head surface 34A that has been dividedinto a first region 52A, a second region 52B, a third region 52C, and afourth region 52D. Each of these regions 52A-52D has a width that isless than the width of the rail head surface 34A in divided image 50.The percentage width of each of the regions 52A-52D in the divided image50 of the rail head surface 34A generally corresponds with the widths ofphysical areas of the rail head surface 34A itself. For example, whenviewing the rail head surface 34A, the inner n % of the width of therail head surface 34A may be the area where a large portion of thecontact between the wheel and the rail head surface 34A occurs. As such,this area may be the most important area for analysis purposes.Generally, the inner n % of rail head surface 34A in the image 40 of therail head surface (and thus the area that would form inner region 52D inthe divided image 50) would correspond to the inner n % of the actualrail head surface 34A. Thus, the inner n % of the rail head surface 34Ain the image 40 can be designated as the fourth region 52D in thedivided image 50.

The correspondence between areas of the rail head surface 34A of theactual rail 26A and areas of the rail head surface 34A in the image 40is generally dependent upon the angle of the cameras relative to theirrespective vertical axes. For example, if the camera is directly abovethe rail 26A, the inner n % of the rail head surface 34A will generallycorrespond to the inner n % of the rail head surface 34A in the image40. However, when the camera is disposed at angle relative to the rail26A (and thus closer to the inner edge of the rail head surface 34A thanto the outer edge of the rail head surface 34A), the inner n % of therail head surface 34A may occupy a larger portion of the field of viewof the camera. The resulting image 40 that can be produced of the railhead surface 34A may be skewed, in that the inner n % of the rail headsurface 34A appears to occupy a percentage of the width of the rail headsurface 34A in the image 40 that is larger than n %. This is because theinner n % of the rail head surface 34A is closer to the camera.Similarly, the outer areas of the rail head surface 34A may appear tooccupy a correspondingly smaller percentage of the rail head surface 34Ain the image 40 than they actually do, because the outer areas of therail head surface 34A are further away from the camera. As such, thepercentage width that is used to divide image 40 and obtain image 50 mayneed to be adjusted to take into account the angle at which the camerais disposed.

In the implementation of FIG. 4B, the first region 52A (e.g. the outerregion) has a width of about 40% of the width of the rail head surface34A in the image 40. The second region 52B and the third region 52C caneach have a width of about 20%. The fourth region 52D (e.g., the innerregion) can have a width of about 40%.

Generally, areas closer to the inner edge of the rail head surface 34Awill be assigned to regions having a smaller width than areas closer tothe outer edge of the rail head surface 34A. This allows the inner areasof the rail head surface 34A (e.g., areas that experience more contactwith the wheel of the vehicle traveling along the rail 26A) to beanalyzed in finer detail. In some implementations, the area of theregion nearest the inner edge of the rail head surface 34A can have awidth as a percentage of the width of the rail head surface 34A that isbetween about 5.0% and about 35.0%, between about 10.0% and about 30.0%,about 20.0%, less than about 20.0%, or less than about 50.0%. The areaof the outer region can have a width as a percentage of the width of therail head surface 34A that is between about 30.0% and about 50.0%,between about 40.0% and about 60.0%, about 40.0%, about 50.0%, or about60.0%. The width of the regions between the inner and outer regions canhave a width as a percentage of the width of the rail head surface 34Athat is between about 5.0% and about 35.0%, between about 10.0% andabout 30.0%, about 20.0%, or less than about 20.0%.

Generally, the one or more regions of the rail head surface 34A in thedivided image 50 can have any desired width or configuration. Forexample, the rail head surface 34A may be divided into more or less thanfour regions. The regions can all have equal widths, some of the regionsmay have equal widths while some of the regions have different widths,or all of the regions can have different widths. In someimplementations, the rail head surface 34A in the image 40 is notdivided into multiple regions at all. Instead, the processors analyzethe whole width of the rail head surface 34A without dividing the railhead surface 34A into multiple regions.

In other implementations, the one or more regions of the rail headsurface 34A in the divided image 50 include an outer region nearest theouter edge of the rail head surface that has a width of about 50.0% ofthe width of the rail head surface 34A. The remaining width of the railhead surface 34A can be divided into two or more other regions, eachhaving a width that is less than about 50.0% of the width of the railhead surface 34A. In still other implementations, any of the regions ofthe rail head surface 34A can generally have any width, so long as noregion has a width that is smaller than the width of the inner regionnearest the inner edge of the rail head surface 34A.

In other implementations, one of the regions may overlap with some orall of the other regions. For example, the width of the rail headsurface 34A can be divided into n−l regions, each having a width that isless than the full width of the rail head surface 34A in the image 40.An n^(th) region of the rail head surface 34A can also be identifiedthat has a width equal to the width of the rail head surface 34A in theimage 40, and thus overlaps with all of the other regions of the railhead surface in the divided image 50. Thus, in the implementation shownin FIGS. 4A and 4B, the system could identify a fifth region that spansthe entire width of the rail head surface 34A in the image 40 andoverlaps with each of the regions 52A-52D.

The overlapping region could also overlap with fewer than all of theother regions. For example, the one or more regions could include aninner region, an outer region, one or more interior regions positionedbetween the inner region and the outer region, and an overlappingregion. The overlapping region could overlap with either (i) the innerregion and the one or more interior regions, or (ii) the one or moreinterior regions and the outer region. And in some implementations, theoverlapping region overlaps only with a portion of the width of one ormore other regions, instead of the entire width of the region.

As noted above, in some implementations, the system produces a singleimage 40 that includes the entire length of both the rail head surfaces34A, 34B. The rail head surfaces 34A, 34B in the single image 40 can bedivided into regions along the width of the rail head surfaces 34A, 34Bto create the divided image 50. The single divided image 50 thusincludes the entire length of both the rail head surfaces 34A, 34Bdivided into a plurality of regions. Each discrete elongated portion ofthe rail head surfaces 34A, 34B in the single divided image 50 can beanalyzed separately. In other implementations, individual images 40 areproduced of one or more discrete elongated portions of rail headsurfaces 34A, 34B. The rail head surfaces 34A, 34B in the individualimages 40 can be divided to create individual images 50.

Regardless of how the image 40 of the rail head surface 34A is dividedto obtain the divided image 50, defects in the rail head surface 34A canbe identified within the regions 52A-52D of the divided image 50. Theseidentified defects can be used to determine information about theregions 52A-52D. The defects that can be identified include cracks,pitting defects (which may be depressions defined in the rail headsurface 34A), grinding marks (marks left by rail grinding machines usedto perform maintenance on the rails), flaking or spalling (pieces ofsurface material detaching from the rail head surface 34A), or otherdefects. The processors can analyze these defects to determine a numberof different properties of the defects and metrics related to the railhead surface 34A.

For example, the divided image 50 can be analyzed to determine the sizeof the defects. For cracks identified in the portion of the rail headsurface 34A, a number of properties of the cracks can be identified,such as the length of the cracks, the width of the cracks, or an angleof the cracks relative to a reference axis. In some implementations, theangle of the cracks is relative to transverse axis B of FIGS. 4A and 4B,e.g., the axis extending between the left rail 26A and the right rail26B. In other implementations, the angle of the cracks is relative tolongitudinal axis C of FIGS. 4A and 4C, e.g., the axis extending alongthe length of the rails 26A, 26B. From the detected length and width ofthe cracks, the system can determine the area of each crack identifiedin the rail head surface 34A. Similarly, the system can analyzeidentified pitting defects or other identified defects to determine thearea of those defects.

To identify defects such as cracks, a spatial filter is first applied tothe divided image 50 of the rail head surface 34A. The spatial filterscan include edge-related filters and center-surround box filters toidentify potential cracks and other damage areas. Next, the cumulativedistribution of the response values of all of the applied filters isused to identify potential areas in the divided image 50 for furtherprocessing. A connected-component analysis and further filtering isapplied to these identified areas to identify the defects. The furtherfiltering can be based on known properties of potential defects, e.g.,minimum or maximum major axis length or aspect ratio.

The system is also configured to identify and filter out grinding markson the rail head surface 34A. Grinding marks are generally notindicative of damage to the rail head surface 34A that requires repairor replacement. By filtering out the grinding marks identified on therail head surface 34A, the system ensures that the grinding marks do notcontribute to the metrics that are calculated. For example, if thegrinding marks are not filtered out by the system, the metrics mayindicate that the rail head surface 34A has more damage than it actuallydoes. This could lead to unnecessary and expensive repairs. Similarly,the presence of the grinding marks could also skew the metrics in theopposite direction, such that the metrics indicate that the rail headsurface 34A has less damage than it actually does.

After (i) identifying defects within each region of the divided image 50of the rail head surface 34A and (ii) determining a number of propertiesrelated to the identified defects, the system can calculate a number ofdifferent metrics for each region 52A-52D of the portion of the railhead surface 34A. The metrics can thus be calculated for regions thathave a width less than the width of the rail head surface 34A and do notoverlap with any other regions, regions that have a width less than thewidth of the rail head surface 34A and do overlap with some or all ofone or more other regions, regions that have a width equal to the widthof the rail head surface 34A and overlap with all of the other regions,or any other region in the divided image 50.

A first metric that the system can calculate is the crack density withina region. The crack density is defined as the area of all cracksidentified in the region divided by the area of the region. Thus, todetermine the crack density of the region, the system first identifiesall cracks in the rail head surface 34A within the region. Next, thesystem determines the area of each of cracks identified within theregion. The area of each of the cracks is added together to determine atotal crack area within the region. By then taking the ratio of (i) thetotal crack area within the region (e.g., the sum of each of the cracksidentified within the region) to (ii) the area of the region, the crackdensity of the region is determined. The units of the crack densitymetric can be a percentage between 0 and 100, or a dimensionless valuebetween 0 and 1.

A second metric that the system can calculate is the average crack anglewithin a region. The average crack angle is calculated by firstdetermining the angle of every crack identified within the region withrespect to the reference axis. The angle of each identified crack isthen added together, and the result is divided by the total number ofcracks identified within the region. This gives the average crack anglewithin the region. The units of the average crack angle metric can bedegrees, radians, or any other unit suitable angular unit.

A third metric that the system can calculate is the average crack widthof a region. The average crack width of the region is determined byadding the width of each crack identified in the rail head surfacewithin the region, and dividing that sum by the number of cracksidentified in the rail head surface 34A within the region. The averagecrack width metric can have units of millimeters or any other suitableunit of distance.

A fourth metric that the system can calculate is the pitting density ofa region. The pitting density of a region is determined in a similarfashion as the crack density of a region. First, the system determinesthe area of each of the pitting defects identified within the region.The area of each of the pitting defects is added together to determinethe total pitting defect area within the region. By then taking theratio of (i) the total pitting defect area within the region (e.g., thesum of each of the pitting defects identified within the region) to (ii)the area of the region, the pitting defect density of the region isdetermined. Similar to the crack density metric, the units of thepitting defect density metric can be a percentage between 0 and 100, ora dimensionless value between 0 and 1.

A fifth metric that the system can calculate is the surface damagedensity of a region. The surface damage density of a region iscalculated in a similar fashion of the crack density or the pittingdefect density. However, instead of limiting the metric to only cracksor only pitting defects, the system determines the area of any type ofdefect identified within the region, including cracks, pitting defects,and all other types of defects. The area of each of the defects is addedtogether to determine the total defect area within the region. By thentaking the ratio of (i) the total defect area within the region to (ii)the area of the region, the surface damage density of the region iscalculated. Similar to the crack density metric and the pitting defectdensity metric, the units of the surface damage density metric can be apercentage between 0 and 100, or a dimensionless value between 0 and 1.

A sixth metric that the system can calculate is known as a surfaceregion index. Multiple types of surface region index metrics can becalculated. A first type of surface region index is the weighted averageof multiple metrics for the same region. In one example, the systemcould assign weights to each of (i) the crack density metric of a firstregion, (ii) the average crack angle metric of the first region, (iii)the average crack width metric of the first region, and (iv) the surfacedamage density metric of the first region. The resulting weighted valuescan be added together to obtain the surface region index for the region.Generally, any combination of any metrics can be used to calculate thefirst type of surface region index metric.

The first type of surface region index can be calculated for any of theindividual regions that the image of the portion of the rail headsurface 34A may be divided into. This includes regions that have a widthless than the width of the rail head surface 34A and do not overlap withany other regions, regions that have a width less than the width of therail head surface 34A and do overlap with some or all of one or moreother regions, regions that have a width equal to the width of the railhead surface 34A and overlap with all of the other regions, or any otherregion.

With this first type of surface region index, different metrics may beassigned different weights depending on which region of the portion ofthe rail head surface 34A is being analyzed. Some metrics may be moreimportant in different regions of the rail head surface 34A depending onwhat type of damage is indicated by what metric. For example, whenlooking at the inner region of the rail head surface 34A, the crackdensity metric may be more determinative of whether the rail 26A (or atleast the inner region of the rail head surface 34A) needs to berepaired or replaced than the average crack angle metric. Thus, whencalculating the first type of surface region index for this innerregion, the crack density metric can be given a higher weight than theaverage crack angle metric. This first type of surface region index isgenerally dimensionless

A second type of surface region index metric is a weighted sum of thesame metric for multiple regions of the portion of the rail head surface34A. For example, the system can determine the average crack width ofeach region in an image, assign a weight to the average crack widthmetric for each region, and then add the weighted average crack widthmetrics. As with the first type of surface region index, the weightingof the individual components can be adjusted based on the metric beingused and the individual regions. The value of a given metric may be moreindicative of whether the rail needs to be repaired or replaced when itis determined for an inner region (where more of the contact between thewheel and the rail head surface 34A occurs) than other regions. Thissecond type of surface region index is also generally dimensionless.

A third type of surface region index that can be calculated is theweighted sum of different metrics for different regions. For example,the third type of surface region index could be the weighted sum of (i)the crack density of a first region, (ii) the average crack angle of asecond region, (iii) the average crack width of a third region, and (iv)the surface damage density of a fourth region. Generally, any of themetrics can be used for any of the different regions, and can beweighted in any combination. This third type or surface region index isalso generally dimensionless. For any of the three types of surfaceregion indices, the different metrics and regions can be weighted invarious different combinations. Generally, depending on the rail systembeing analyzed and the preferences of the user, any metric can be givenany weight in any region.

Any of the metrics can also be modified and/or combined in various waysto reveal different information about the rail head surface 34A. Forexample, instead of calculating the average crack angle metric andaverage crack width metric for a given region, the system couldcalculate the average crack angle in the region for any cracks that havea width larger than a pre-defined threshold.

All of the above-described metrics can be calculated for each discreteelongated portion of the rail head surface 34A, 34B having a unit lengthl, and for each rail 26A, 26B of the track. Thus, for a system thatanalyzes a total length L of a track that includes two rails 26A, 26B,the system can produce images of L/l discrete elongated portions of therail head surfaces 34A, 34B of each rail 26A, 26B, for a total of 2*L/limages. If each discrete elongated portion of the rail head surfaces34A, 34B is divided into n regions (which can include non-overlappingand overlapping regions, as well as the entire width as a region) and mmetrics are calculated for each region, the total number of individualmetrics that are calculated is equal to 2*n*m*L/l. For a system thatanalyzes a track having r number of rails, a total of r*n*m*L/l metricscan be calculated. In addition, the metrics could also include agrinding mark indicator showing the presence or absence grinding marks.Generally, a single grinding mark indicator can be determined orcalculated for each rail, resulting in a total of (r*n*m*L/l)+r metrics.

Referring now to FIG. 5, the electronic display device 22 can display animage 60 that includes one or both of the rail head surfaces 34A, 34B,along with a variety of other information. In some implementations,image 60 shows only rail head surface 34A, and is generally equivalentto image 40 discussed herein. In other implementations, image 60 showsboth rail head surfaces 34A and 34B, and is generally equivalent to animage 40 of the rail head surface 34A and another image 40 of the railhead surface 34B. In other implementations, image 60 is different fromother produced images 40 that show the rail head surfaces 34A, 34B. Inother implementations, the electronic display device 22 displays onlythe image 60 of one or both of rail head surfaces 34A, 34B. In stillother implementations, the electronic display device 22 displays onlyinformation about the rails 26A, 26B and the rail head surfaces 34A,34B. As discussed herein, this information can be graphs that show thevalue of the calculated damage metrics along the entire length of therail head surfaces 34A, 34B.

In the implementation of FIG. 5, image 60 shows rail head surface 34Aand rail head surface 34B. Image 60 generally shows a single discreteelongated portion of both rail head surfaces 34A and 34B, as well as anydefects within in the rail head surfaces 34A, 34B within the singlediscrete elongated portion. The defects in the rail head surfaces 34A,34B are generally visible to the user, allowing the user to visuallyanalyze the rail head surfaces 34A, 34B. While the image 60 in FIG. 5shows both rail head surface 34A and rail head surface 34B, image 60 cangenerally include some or all of the rails of a multi-rail system, orthe only rail of a single-rail system. Furthermore, in someimplementations, image 60 shows multiple discrete elongated portions ofthe rail head surfaces 34A, 34B.

The electronic display device 22 can also display cross sectional-imagesthe rails in a vertical plane. For example, the electronic displaydevice 22 displays cross-sectional image 62A of rail 26A. andcross-sectional image 62B of rail 26B. Each of the cross-sectionalimages 62A, 62B are taken at a cross-section located at a certain pointalong the length of the rails 26A, 26B. These cross-sectional images 62Aand 62B, or rail profile images, show the rail base 28A and 28B, therail web 30A and 30B, and the rail head 32A and 32B at a given locationalong the length of the rails 26A, 26B.

The cross-sectional images 62A, 62B can be obtained by system 10 usingcameras 14A, 14B, or could be obtained by a separate imaging system. Thecross-sectional images 62A, 62B illustrate features of the rails 26A,26B, such as the angle each rail 26A, 26B is tilted at relative to theground. This feature of the rails 26A, 26B is known as the cant. Thecross-sectional images 26A, 26B can also show the degree to which therails 26A, 26B have been worn away as compared to a new rail. Theelectronic display device 22 can display one or both cross-sectionalimages 62A, 62B alone, or in combination with one or both of the image60 of the rail head surfaces 34A, 34B and the information about therails 26A, 26B and the rail head surfaces 34A, 34B.

The electronic display device 22 can display graphs 64A-64E of a varietyof different properties of the rails 26A, 26B. These properties could bestructural properties related to the size, orientation, etc. of therails, or other properties. Each graph 64A-64E plots the value of agiven property against length of the rails 26A, 26B. Graph 64A shows thecurvature of the rails 26A, 26B. The curvature of the rails 26A, 26B isdetermined by forming a reference chord that connects two points along acurve of rails 26A, 26B. Two radii are formed between the center of thecurve of the rails 26A, 26B, and the respective endpoints of thereference chord. The angle between the two radii is defined as thecurvature of the rails 26A, 26B.

Graph 64B shows the crosslevel of the rails 26A, 26B. The crosslevel ofthe rails 26A, 26B is the elevation difference between the rail head 32Aof rail 26A and the rail head 32B of rail 26B. Graph 64C shows the gageof the rails 26A, 26B. The gage of the rails 26A, 26B is the horizontaldistance between the inner edge of rail 26A and the inner edge of rail26B. Graph 64D shows the cant of rail 26A. Graph 64E shows the cant ofrail 26B. Generally, the electronic display device 22 can display anynumber of graphs that show properties of the rails 26A, 26B.

The graphs of the properties of the rail can also include graphs ofwhether grinding marks are present in rail head surfaces 34A, 34B. Insome implementations, these graphs are a binary indicator of whethergrinding marks are present. In these implementations, the value of thegraph for every location along the length of the rail head surfaces 34A,34B is generally a high value (indicating the presence of grindingmarks) or a low value (indicating the absence of grinding marks). Insome implementations, a high value could indicate the absence ofgrinding marks, while a low value could indicate the presence ofgrinding marks. In still other implementations, the value of the graphsof the grinding marks can be on a continuous scale that can indicate theseverity of the grinding marks. The properties of rails 26A, 26B,including the structural properties and grinding marks, can bedetermined by system 10, or could be determined by one or more otherseparate systems.

The electronic display device 22 can also display graphs 66A-66F of themetrics that are calculated for the different regions defined in theimages 40 of the rail head surfaces 26A, 26B. Graph 66A shows the valueof the crack density metric in the first region of rail 26A, e.g., theleft rail. Graph 66B shows the value of the surface damage densitymetric in the second region of the left rail 26A. Graph 66C shows thevalue of the crack density metric in the third region of the left rail26A. Graph 66D shows the value of the crack density metric in the firstregion of the right rail 26B. Graph 66E shows the value of the surfacedamage density metric in the second region of the right rail 26B.Finally, graph 66D shows the value of the crack density metric in thethird region of the right rail 26B. The electronic display device candisplay any number of graphs that show the calculated metrics ofdifferent regions of the rails 26A, 26B.

All of the graphs 64A-64E and 66A-66F can have a common x-axis thatcorresponds to a location along the length of the rail head surfaces34A, 34B. For the graphs 66A-66F that show the calculated metrics, eachdata point corresponds to the value of a metric for a single discreteelongated portion of the rail head surfaces 34A, 34B. In someimplementations though, the rail properties are measured at individuallocations along the length of the rail head surfaces 34A, 34B, and notfor discrete elongated portions of the rail head surfaces 34A, 34B. Andoftentimes, the rail properties are measured at multiple locations thatfall within a single discrete elongated portion of the rail headsurfaces 34A, 34B giving rise to a single value of the calculatedmetrics.

Thus, a data point in one of the graphs 64A-64E of the rail propertiesat a single discrete point on the x-axis corresponds to the value ofthat property at the location along the length of the rail head surfaces34A, 34B that the single discrete point on the x-axis represents. Thedata point in one of the graphs 66A-66F of the calculated metrics atthat same single discrete point on the x-axis corresponds to the valueof that calculated metric for a discrete elongated portion of the railhead surfaces 34A, 34B that includes the location that the singlediscrete point on the x-axis represents. That location could be locatedat the beginning of the respective discrete elongated portion of therail head surfaces 34A, 34B, at the end of the respective discreteelongated portion of the rail head surfaces 34A, 34B, the middle of therespective discrete elongated portion of the rail head surfaces 34A,34B, or at any other location within the respective discrete elongatedportion of the rail head surfaces 34A, 34B, including the beginning orend of the respective discrete elongated portion of the rail headsurfaces 34A, 34B.

In some implementations, the rail properties could be measured for adiscrete elongated portion of the rail head surfaces 34A, 34B.Similarly, some metrics related to the defects are measured atindividual locations along the rail head surfaces 34A, 34B. Generally,any property, characteristic, or metric related to the rails 26A and26B—whether it is measured at individual locations along the length ofthe rail head surfaces 34A, 34B or for a discrete elongated portion—canbe displayed by the electronic display device 22 and have a commonx-axis with any other property, characteristic, or metric displayed bythe electronic display device 22.

The electronic display device 22 can further display one or more visualmarkers that link a location along the length of the rail head surfaces34A, 34B displayed in image 60 with (i) the value of all the railproperties of graphs 64A-64-E at that same location, and (ii) the valueof all of calculated metrics of graphs 66A-66F for a respective discreteelongated portion of the rail head surfaces 34A, 34B that includes thatsame location.

In the implementation of FIG. 5, the one or more visual markers includea horizontal marker 68A and a vertical marker 68B. The horizontal marker68A can overlaid at a specific location along one or both of rail headsurfaces 34A, 34B in image 60. The vertical marker 68B is overlaid onsome or all of the graphs 64A-64E and 66A-66F at a point along thex-axis corresponding to a location along the length of the rail headsurfaces 34A, 34B. The horizontal marker 68A and the vertical marker 68Bboth correspond to the same location along the length of the rail headsurfaces 34A, 34B. This allows the user to easily view the defectswithin the rail head surface 34A, 34B of either rail 26A, 26B, and thendetermine the values of the rail properties and the calculated metricsrelated to those defects.

The user can interact with either of the visual markers 68A, 68B to movethem to different locations on the rail head surfaces 34A, 34B. When theuser or the system causes either visual marker 68A, 68B to be overlaidat a new location along the length of the rail head surfaces 34A, 34B,the other visual marker 68B, 68A can automatically be update such thatit is overlaid at the same location. For example, while viewing all ofthe information displayed by the electronic display device 22, the usermay notice a defect in the rail head surfaces 34A, 34B in image 60. Byinteracting with the horizontal marker 68A so that it is overlaid on theimage 60 at or near the defect the user is interested in, the verticalmarker 68B and/or the graphs 64A-64E and 66A-66F can move so that thevertical marker 68B is at or near the position along the x-axiscorresponding to where the defect in the rail head surfaces 34A, 3B is.The vertical marker 68A will then show the user the properties of therails 26A, 26B and the value of the calculated metrics where the defectis.

Similarly, if the user identifies any data points of interest in any ofthe graphs 64A-64E and 66A-66F, the user can interact with the verticalmarker 68B and/or the graphs 64A-64E and 66A-66F until the verticalmarker 68B is at or near the data points of interest. Following this,the horizontal marker 68A and/or the image 60 can automatically updateso that the horizontal marker 68A is overlaid on the image 60 at or nearthe location along the length of the rail head surfaces 34A, 34B thatgave rise to the data points of interest. Thus, the visual markers 68A,68B allow the user to quickly link the qualitative characteristics ofthe rail head surfaces 34A, 34B (e.g., defects in the rail head surfaces34A, 34B visible in the images) with the quantitative characteristics ofthe rail head surfaces 34A, 34B (e.g., the value of the positionalcharacteristics and the calculated metrics).

In some implementations, the user can move the horizontal marker 68A todifferent locations along the rail head surfaces 34A, 34B while the railhead surfaces 34A, 34B remain stationary. In other implementations, theuser can cause the rail head surfaces 34A, 34B to move while thehorizontal marker 68A remains stationary. In still otherimplementations, both the horizontal marker 68A and the rail headsurfaces 34A, 34B can move.

Similarly, in some implementations, the user can move the verticalmarker 68B to different locations along the x-axis while the graphs64A-64E and 66A-66F remain stationary. In other implementations, theuser can cause the graphs 64A-64E and 66A-66F to move while the verticalmarker 68B remains stationary. In still other implementations, both thevertical marker 68B and the graphs 64A-64E and 66A-66F can move.

The longitudinal length of the rail head surfaces 34A, 34B that isdisplayed in image 60 can be adjusted by the user. The length that isdisplayed in image 60 can generally range from only a part of a singlediscrete elongated portion, up to the entire length of the track thathas been analyzed. Similarly, the longitudinal length represented by thex-axis of the graphs 64A-64E and 66A-66F is also adjustable by the user.The length represented by the x-axis of the graphs can have a similarrange as the image 60, from only a part of a single discrete elongatedportion, up to the entire length of the track that has been analyzed. Insome implementations, the user can adjust the x-axis of each of thegraphs individually such that the graphs may display data for differentlongitudinal lengths.

In some implementations, the electronic display device 22 is configuredto automatically update the cross-sectional images 62A, 62B of the rails26A, 26B. Thus, when the user causes the horizontal marker 68A to beoverlaid at a new location along the length of the rail head surfaces34A, 34B, the electronic display device 22 can automatically update thecross-sectional images 62A, 62B so that they show the profile of therails 26A, 26B at the new location. Similarly, when the user causes thevertical marker 68B to intersect with the x-axis of the graphs 64A-64Eand 66A-66F at a new point, the electronic display device 22 canautomatically update the cross-sectional images 62A, 62B so that theyshow the profile of rails 26A, 26B at that location represented by thenew point along the x-axis.

In some implementations, the user can continuously scroll along railhead surfaces 34A, 34B in image 60 to view other locations along thelength of the rail head surfaces 34A, 34B. In other implementations, theimage 60 can be advanced in increments from one elongated portion of therail head surfaces 34A, 34B to the next elongated portion of the railhead surfaces 34A, 34B. Similarly, the user can control how much of therail head surfaces 34A, 34B are shown in the image 60, and how much ofthe length of the rails 26A, 26B and the rail head surfaces 34A, 34B arerepresented in the graphs 64A-64E and 66A-66F.

Referring now to FIG. 6, a method 100 for visualizing and quantifyingsurface damage on a railroad track is illustrated. At step 102, camerasdisposed adjacent to the rails of the railroad track generate image datathat is reproducible as one or more images of the rail head surfaces ofthe rails. Any number of cameras can be used to generate the image data.For tracks that have multiple rails, multiple cameras can be used togenerate multiple sets of image data.

At step 104, an image of the rail head surface is produced from thegenerated image data. This image generally shows an elongated portion ofthe rail head surface of the one or more rails. An image of the sameelongated portion of the rail head surface of each rail of the railroadtrack can be generated. At step 106, the image of the portion of therail head surface of each image is divided into a plurality of regions.Generally, the rail head surface is divided along its width such thateach region has a length equal to the length of the elongated portion ofthe rail head surface, and each region has a width less than the widthof the rail head surface. However, one or more of the regions canoverlap with other regions. For example, one of the regions can span theentire width of the rail head surface and overlap with all of the otherregions. Other overlapping regions can have a width less than the widthof the rail head surface and overlap with some or all of the remainingregions.

At step 108, the divided image of the rail head surface is analyzed toidentify defects in the rail head surface within each of the regions.The defects could be cracks, pitting defects, or any other type ofdefects. Grinding marks can also be identified on the rail head surface.As noted herein, a defect identified in the surface of the rail does notrequire the rail to be repaired or replaced. At step 110, the systemdetermines information associated with the identified defects. Thedetermined information associated with the defects can include a numberof metrics that quantify various properties of the defects in the railhead surface. Each metric can be calculated for each individual region.Some metrics include the crack density, the average crack angle, theaverage crack width, the pitting density, the surface damage density, ora surface region index. These metrics serve to indicate the condition ofthe rail head surfaces.

At step 112, an electronic display device can display one or both of theimage of the rail head surface and the information associated with thedefects. The image of the rail head surface shows defects that thesystem has identified in the rail head surface. The image may show asingle elongated portion of the rail head surface, or may show multipleelongated portions of the rail head surface. The displayed informationcan include graphs of the calculated metrics along the longitudinallength of the rail, as well as graphs of other information related tothe rail. The electronic display device can include visual markers thatlink locations along the longitudinal length of the rail in the imagewith the value of the calculated metrics at or near the locations. Theelectronic display device can also display cross-sectional images of therails.

While the present disclosure has been described with reference to one ormore particular embodiments or implementations, those skilled in the artwill recognize that many changes may be made thereto without departingfrom the spirit and scope of the present disclosure. Each of theseembodiments or implementations and obvious variations thereof iscontemplated as falling within the spirit and scope of the presentdisclosure. It is also contemplated that additional embodimentsimplementations according to aspects of the present disclosure maycombine any number of features from any of the embodiments describedherein.

What is claimed is:
 1. A method comprising: receiving image datagenerated by a camera disposed adjacent to a rail of a railroad track,the image data being reproducible as an image of a surface of the rail;dividing the image of the surface of the rail into a plurality ofelongated portions across a width of the surface of the rail; analyzingthe image to identify one or more defects within each of the pluralityof elongated portions of the surface of the rail; determining a value ofat least one metric for each of the plurality of elongated portions ofthe surface of the rail, the at least one metric being associated withthe identified one or more defects within each of the plurality ofelongated portions of the surface of the rail; and causing an electronicdisplay device to display information indicative of the at least onemetric for each of the plurality of elongated portions of the surface ofthe rail.
 2. The method of claim 1, wherein the analyzing the imageincludes dividing at least one of the plurality of elongated portions ofthe surface of the rail in the image into a plurality of regions along awidth of the surface of the rail such that each of the plurality ofregions in the image has a length generally equal to a length of the atleast one elongated portion of the surface of the rail in the image. 3.The method of claim 2, wherein one region of the plurality of regionshas a width equal to a width of the at least one elongated portion ofthe surface of the rail in the image, and each remaining region of theplurality of regions of the image has a width less than the width of theat least one elongated portion of the surface of the rail in the image,and a sum of the width of each of the remaining regions of the pluralityof regions is equal to the width of the at least one elongated portionof the surface of the first rail in the image.
 4. The method of claim 1,wherein the one or more defects include one or more cracks, pitting, orboth, and the at least one metric associated with the identified one ormore defects within a first one of the plurality of elongated portionsof the surface of the rail includes a crack density of the identifiedone or more cracks, an average crack angle of the identified one or morecracks, an average crack width of the identified one or more cracks, apitting density of the identified pitting, a surface damage density, asurface region index, or any combination thereof.
 5. The method of claim4, wherein (i) the crack density of the identified one or more cracks isgenerally equal to a ratio of (a) a sum of an area of each of theidentified one or more cracks within the first one of the plurality ofelongated portions to (b) an area of the first one of the plurality ofelongated portions, (ii) the average crack angle of the identified oneor more cracks is generally equal to an average angle of the identifiedone or more cracks within the first one of the plurality of elongatedportions with respect to a reference axis, (iii) the average crack widthof the identified one or more cracks is generally equal to an averagecross-sectional width of the identified one or more cracks within thefirst one of the plurality of elongated portions, (iv) the pittingdensity of the identified pitting is generally equal to a ratio of (a) asum of an area of the identified pitting within the first one of theplurality of elongated portions to (b) an area of the first one of theplurality of elongated portions, (v) the surface damage density of theidentified one or more defects is generally equal to a ratio of (i) asum of an area of each of the identified one or more defects within thefirst one of the plurality of elongated portions to (ii) an area of thefirst one of the plurality of elongated portions, and (vi) the surfaceregion index is generally equal to a weighted sum of at least two of thecrack density, the average crack angle, the average crack width, thepitting density, or the surface damage density.
 6. The method of claim5, further comprising causing the electronic display device to display afirst visual marker and a second visual marker on the graph, wherein thefirst visual marker indicates a first location in the image along thesurface of the rail, and wherein the second visual marker indicates thevalue of the at least one metric at a corresponding one of the pluralityof elongated portions of the surface of the rail that includes the firstlocation.
 7. The method of claim 1, wherein the displayed informationincludes a graph indicative of the at least one metric for each of theplurality of elongated portions of the surface of the rail.
 8. Themethod of claim 7, wherein the at least one metric includes a firstmetric and a second metric different from the first metric, and whereinthe second visual marker indicates the value of both the first metricand the second metric for one of the plurality of elongated portions ofthe surface of the first rail.
 9. The method of claim 1, wherein thecamera is coupled to a transport device configured to move along therailroad track.
 10. The method of claim 1, further comprising causingthe electronic display device to display at least a portion of theimage.
 11. The method of claim 1, further comprising: analyzing theimage to identify one or more grinding marks within each of theplurality of elongated portions of the surface of the rail; and whereinthe determining the value of the at least one metric includes filteringthe identified one or more grinding marks.
 12. A method comprising:receiving first image data generated via a first camera disposedadjacent to a first rail of a railroad track, the first image data beingreproducible as a first image of a portion of a surface of the firstrail; receiving second image data generated via a second camera disposedadjacent to a second rail of the railroad track, second image data beingreproducible as a second image of a portion of a surface of the secondrail; dividing the first image of the portion of the surface of thefirst rail into a first plurality of regions across a width of thesurface of the first rail; dividing the second image of the portion ofthe surface of the second rail into a second plurality of regions acrossa width of the surface of the second rail; analyzing the divided firstimage to identify, within each of the first plurality of regions, one ormore defects in the portion of the surface of the first rail; analyzingthe divided second image to identify, within each of the secondplurality of regions, one or more defects in the portion of the surfaceof the second rail; determining information associated with theidentified one or more defects in the portion of the surface of thefirst rail and the identified one or more defects in the portion of thesurface of the second rail; and causing an electronic display device todisplay the determined information associated with the identified one ormore defects in the portion of the surface of the first rail, thedetermined information associated with the identified one or moredefects in the portion of the surface of the second rail, or both. 13.The method of claim 12, wherein the first camera, the second camera, orboth are coupled to a transport device configured to move along therailroad track.
 14. The method of claim 12, further comprising causingthe electronic display device to display at least a portion of the firstimage, at least a portion of the second image, or both.
 15. The methodof claim 14, further comprising causing a first visual marker and asecond visual marker to be overlaid on the first graph and the secondgraph.
 16. The method of claim 15, wherein the information associatedwith the identified one or more defects in the portion of the surface ofthe first rail is indicative of a crack density of the identified one ormore cracks, an average crack angle of the identified one or morecracks, an average crack width of the identified one or more cracks, apitting density of the identified pitting, a surface damage density, asurface region index, or any combination thereof.
 17. The method ofclaim 12, further comprising causing the electronic display device todisplay (i) a first graph indicative of the determined informationassociated with the with the identified one or more defects in theportion of the surface of the first rail, (ii) a second graph indicativeof the determined information associated with the with the identifiedone or more defects in the portion of the surface of the second rail, orboth (i) and (ii).
 18. The method of claim 12, wherein the one or moredefects include one or more cracks, pitting, or both.